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Applications Of Public Global Optimization Software To Difficult Econometric Functions

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  • Max Jerrell

    (Northern Arizona University)

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    Abstract

    The location of the global optimum is very desirable in nonlinear parameter estimation problems. Using a local rather than global optimum most likely will result in inconsistent estimators. While many commercial software packages have good optimization routines, these usually only find local optima. Some of these commercial packages also have only limited capability to express constraints. Likewise, these packages often do not allow users to define their own functions.There is a large and growing amount of freely available software that has a good chance of locating the global optimum. New techniques are being developed and existing methods are being refined. Much of the software can be downloaded over the Internet.This research will survey this software and compare different techniques. Methods of obtaining the software will also be discussed. Finally some of the more promising software will be applied to difficult econometric functions (GARCH models and disequilibrium models).

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    Bibliographic Info

    Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2000 with number 161.

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    Date of creation: 05 Jul 2000
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    Handle: RePEc:sce:scecf0:161

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    Postal: CEF 2000, Departament d'Economia i Empresa, Universitat Pompeu Fabra, Ramon Trias Fargas, 25,27, 08005, Barcelona, Spain
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    1. Goffe, William L. & Ferrier, Gary D. & Rogers, John, 1994. "Global optimization of statistical functions with simulated annealing," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 65-99.
    2. Fair, Ray C & Jaffee, Dwight M, 1972. "Methods of Estimation for Markets in Disequilibrium," Econometrica, Econometric Society, vol. 40(3), pages 497-514, May.
    3. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
    4. Maddala, G S & Nelson, Forrest D, 1974. "Maximum Likelihood Methods for Models of Markets in Disequilibrium," Econometrica, Econometric Society, vol. 42(6), pages 1013-30, November.
    5. Goffe, William L & Ferrier, Gary D & Rogers, John, 1992. "Simulated Annealing: An Initial Application in Econometrics," Computer Science in Economics & Management, Society for Computational Economics, vol. 5(2), pages 133-46, May.
    6. Fair, Ray C & Kelejian, Harry H, 1974. "Methods of Estimation for Markets in Disequilibrium: A Further Study," Econometrica, Econometric Society, vol. 42(1), pages 177-90, January.
    7. Mayer, Walter J., 1989. "Estimating disequilibrium models with limited a priori price-adjustment information," Journal of Econometrics, Elsevier, vol. 41(3), pages 303-320, July.
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